Universiteit van Amsterdam, Korteweg - de Vries Institute for Mathematics

Position ID:

1729-POSTDOC1 [#28006]

Position Title:

Postdoc position: Singular Learning Theory for Machine Learning Models

Position Type:

Postdoctoral

Position Location:

Amsterdam, Noord-Holland 1091, Netherlands (Kingdom of the)

Subject Areas:

Singular Learning Theory (SLT), Machine Learning

Appl Deadline:

2026/02/28 11:59PM help popup

(posted 2026/01/22, listed until 2026/03/01)

Position Description:

Introduction Singular Learning Theory (SLT) is a mathematical framework for analysing statistical models that do not follow the classically made regularity assumptions (which would lead to asymptotic normality, etc.). Such singular models include many models from statistical physics as well as almost all modern (“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding of the parameter space in relation to the statistical model. One of the main goals of SLT is to quantify the complexity of such models w.r.t. the data generating process (and some prior probability distribution). SLT and the estimation of such quantities has recently led to many applications, ranging from model selection and uncertainty quantification, over detecting phase transitions in machine learning models during training, the finding of interpretable substructures to the explainability of general learning behaviour of such machine learning models, etc. In this project, we want to build upon the recent developments in the field and either push the boundaries of SLT on the mathematical foundational theory side, extend SLT to new learning frameworks (e.g. variational inference or reinforcement learning, etc.) and/or apply it to modern machine learning models like large language models or diffusion models, etc. If you want to join the mission of unlocking the “geometry of artificial intelligence” then please apply!

This is what you will do You are expected to: • take an active role in the research project either in the development of the mathematical theory of SLT and/or through novel applications of SLT in the machine learning domain. • publish and present your findings in academic peer-reviewed journals, international workshops and/or conferences. • support the teaching activities at the faculty (up to 10% of the time).

What we ask of you • A PhD in Machine Learning, Computer Science, Mathematics, Statistics, Physics or a closely related field. (In case, you have finished a PhD thesis, and you are just awaiting your PhD defence, please also apply.) • Enthusiasm for the scientific process: formulating and investigating hypotheses, either mathematically or by conducting experiments, disseminating findings via writing and oral presentations, etc. • Experience in publishing academic papers in peer-reviewed journals and/or conferences. • Professional command of English, both written and spoken. • Ability both to work independently as well as to cooperate and work effectively within a (possibly interdisciplinary) team of researchers. • Experience in programming and software development. Familiarity with Python and statistical computing libraries, like PyTorch or JAX, etc., would be preferred. • You are a motivational teacher, with an encouraging teaching style.

This is what we offer you We offer a temporary employment contract for 38 hours per week for a period of 18 months. The preferred starting date is as soon as possible. The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 3,345 to € 5,278 (scale 10). This does not yet include the 8% holiday allowance and 8,3% year-end allowance, which will come on top. The UFO profile Researcher/Onderzoeker 4 is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

You will work here The University of Amsterdam (UvA) is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 30,000 students, 6,000 staff members and 3,000 PhD candidates’ study and work in a diverse range of fields, connected by a culture of curiosity.

The Faculty of Science (FNWI) has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The Korteweg-de Vries Instituut voor Wiskunde (KdVI) is the mathematical research institute of the Faculty of Science of the Universiteit van Amsterdam. The KdV Institute offers a stimulating scientific environment in which research focuses mainly within the research programmes (1) Algebra, Geometry and Mathematical Physics, (2) Pure, Applied and Numerical Analysis, and (3) Stochastics and (4) Discrete Mathematics and Quantum Information. It also provides the lecturers and instructors for the mathematics teaching within the Science Faculty. The KdV Institute participates in the NWO research clusters GQT, STAR, NDNS+ and DIAMANT and in the Gravity programme NETWORKS. There is formal (and informal) cooperation with the Centrum Wiskunde & Informatica (CWI), the VU University, and with Eurandom in Eindhoven. KdVI counts about 40 staff members and 50 postdocs and PhD students.

This position will also be affiliated with the AI4Science Lab, which originated out of the Amsterdam Machine Learning Lab (AMLab) at the Informatics Institute (IvI) and which is a cross-institute collaboration at the Faculty of Science aimed at bridging the gap between modern machine learning developments and their applications to the different areas of science.

Want to know more about our organisation? Read more about working at the University of Amsterdam.

If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the button below. We accept applications until and including 28-02-2026. The interviews are expected to take place in March 2026.

If you have any questions or do you require additional information? Please contact: • Dr. Patrick Forré, Associate Professor of Stochastics, KdVI, p.d.forre@uva.nl.

Applications should include the following information (all files besides your cv should be submitted in one single pdf file): • a detailed CV including the months (not just years) when referring to your education and work experience. • a list of publications. • a letter of motivation, including research statement describing your interests in the topic and potential avenues of research (e.g. an idea for an initial project); • the names and email addresses of two references who can provide letters of recommendation (please do not include the letters themselves). • a complete record of your courses, including grades and an explanation of the grading system. • a link to / a copy of the most relevant written work product. Examples: PhD or MSc thesis, research paper (working draft or pre-print is acceptable), course project, blog post, etc. • Optional: A letter providing any additional information not sufficiently highlighted by the other materials.

A knowledge security check can be part of the selection procedure. (for details: national knowledge security guidelines)

We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://werkenbij.uva.nl/en/vacancies/postdoc-position-in-singular-learning-theory-for-machine-learning-models-netherlands-14741 .

Contact: Dr. Patrick Forré, Associate Professor of Stochastics, KdVI

Email: email address

Postal Mail:

: P.O. Box 94248
1090 GE Amsterdam
The Netherlands

Web Page: http://kdvi.uva.nl/